Tool and skills: Proficiency in data analysis tools (e.g., SQL, Python, R) and visualization platforms (e.g., Tableau) is essential. Advanced analytic methods (e.g. data mining, segmentation, logistic regression, Decision Trees) are important. Familiarity with machine learning algorithms and statistical techniques for risk prediction and management is also valuable but not neccesary.
Curiosity: A strong desire to explore, learn, and understand the data deeply to uncover insights and opportunities.
Analytical thinking and skills: Requires the ability to perform complex analyses with quick turnarounds
Business Understanding: Needs to provide actionable insights to support decision-making.
